Evidence map›Paper›PMID 38206048›Full record

ArticleMicrobiology spectrum2024

Comparison of analytical performance and economic value of two biosurveillance methods for tracking SARS-COV-2 variants of concern.

Nicholas P Pinkhover, Kerriann M Pontbriand, Kelli P Fletcher, Eduardo Sanchez, Kenneth Okello, Liam M Garvey, Alex Pum, Kurvin Li, Gabriel DeOliveira, Teddie Proctor and 4 more

Abstract read
In one paragraph

Article in Microbiology spectrum, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Nicholas P PinkhoverDepartment of Chemistry and Chemical Biology, Life Sciences Testing Center, Northeastern University Innovation Campus, Burlington, Massachusetts, USA.ORCID 0000-0002-8099-6017
Kerriann M PontbriandDepartment of Chemistry and Chemical Biology, Life Sciences Testing Center, Northeastern University Innovation Campus, Burlington, Massachusetts, USA.
Kelli P FletcherDepartment of Chemistry and Chemical Biology, Life Sciences Testing Center, Northeastern University Innovation Campus, Burlington, Massachusetts, USA.
Eduardo SanchezDepartment of Chemistry and Chemical Biology, Life Sciences Testing Center, Northeastern University Innovation Campus, Burlington, Massachusetts, USA.
Kenneth OkelloDepartment of Chemistry and Chemical Biology, Life Sciences Testing Center, Northeastern University Innovation Campus, Burlington, Massachusetts, USA.
Liam M GarveyDepartment of Chemistry and Chemical Biology, Life Sciences Testing Center, Northeastern University Innovation Campus, Burlington, Massachusetts, USA.
Alex PumDepartment of Chemistry and Chemical Biology, Life Sciences Testing Center, Northeastern University Innovation Campus, Burlington, Massachusetts, USA.
Kurvin LiDepartment of Chemistry and Chemical Biology, Life Sciences Testing Center, Northeastern University Innovation Campus, Burlington, Massachusetts, USA.
Gabriel DeOliveiraDepartment of Chemistry and Chemical Biology, Life Sciences Testing Center, Northeastern University Innovation Campus, Burlington, Massachusetts, USA.
Teddie ProctorThermo Fisher Scientific, Genetic Testing Solutions, South San Francisco, California, USA.
Jelena D M FeenstraThermo Fisher Scientific, Genetic Testing Solutions, South San Francisco, California, USA.
Océane SorelThermo Fisher Scientific, Genetic Testing Solutions, South San Francisco, California, USA.
Manoj GandhiThermo Fisher Scientific, Genetic Testing Solutions, South San Francisco, California, USA.
Jared R AuclairDepartment of Chemistry and Chemical Biology, Life Sciences Testing Center, Northeastern University Innovation Campus, Burlington, Massachusetts, USA.ORCID 0000-0002-3094-1544

Funding

Northeastern University
6 · The paper itself

Abstract

The development of biosurveillance programs with strong analytical performance and economically accessible protocols is essential for monitoring viral pathogens. Throughout the COVID-19 pandemic, whole-genome sequencing (WGS) has been the prevailing technology for SARS-CoV-2 variant of concern (VOC) detection. While WGS offers benefits, it is a lengthy process, financially and technically straining for scalable viral tracking. The aim of this study was to compare the analytical performance and economic feasibility of WGS and PCR mutation panels for distinguishing six known VOCs: Alpha (B.1.1.7 and Q.4), Gamma (P.1), Delta (B.1.617.2 and AY.4.2), and Omicron. (B.1.1.529.1). In all, 78 SARS-CoV-2-positive samples were collected from April to December 2021 at Northeastern University (Cabot Testing Site, Boston, MA, USA) for genotyping PCR and WGS analysis. MagMax Viral/Pathogen II Nucleic Acid Isolation and TaqPath COVID-19 Combo Kits were used for RNA extraction and SARS-CoV-2 confirmation. VOC discrimination was assessed using two TaqMan SARS-CoV-2 single nucleotide polymorphism (SNP) assay layouts, and Ion Torrent WGS. In November 2021, the mutation panel demonstrated marked versatility by detecting the emerging Omicron variant reported by South Africa. SNP panel analysis yielded the following 78 VOC identifications: Alpha B.1.1.7 (

Indexed as

BiosurveillanceCOVID-19HumansPandemicsSARS-CoV-2genotypingNGSPCRSARS-CoV-2sequencingsurveillancevariants of concern

Identifiers

PMID38206048
PMCPMC10845967

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.